Skip to main content
Wolters Kluwer - PMC COVID-19 Collection logoLink to Wolters Kluwer - PMC COVID-19 Collection
. 2022 Oct 10;65(3):255–260. doi: 10.1097/JOM.0000000000002725

Psychosocial Predictors and Mediators Relating to the Preventive Behaviors of Hospital Workers During the COVID-19 Pandemic in Turkey

Fatma Ülkü Selçuk 1, Semiha Solak Grassie 1
PMCID: PMC9987642  PMID: 36221299

Less than half of the COVID-19 infections are reported to have origins in risky contacts with the patients. Within and outside the hospital, socialization through insufficient preventive measures disseminates the infection considerably. Therefore, understanding the risk factors both within and outside the hospital is crucial for developing policies against any possible pandemics.

Keywords: COVID-19 pandemic, health care workers, vaccination, preventive behaviors, basic human values, Big Five, Dark Triad, early maladaptive schemas

Objective

The aim is to analyze the relation of psychosocial factors to COVID-19 contraction, vaccination, and preventive health behavior in and outside work.

Methods

The questionnaire data from hospital-workers in Turkey is analyzed using independent-samples t-test, logistic regression, linear regression, and mediation analyses. We developed a questionnaire on mask-hygiene-distance measures and also used previously developed scales including the Big Five Personality Questionnaire, Young Schema Questionnaire Short Form 3, Schwartz's Basic Human Values Scale, Short Dark Triad.

Results

The odds of being infected by COVID-19 increases by self-direction. The odds of being vaccinated increases by age and conformity, and decreases by emotional stability. Education predicts certain preventive behaviors at work negatively and outside work positively. Older age, being a woman, having chronic disease, the self-transcendence and conservation values, agreeableness, and conscientiousness predict more preventive behaviors. The self-enhancement and openness to change values, the Dark Triad, and early maladaptive schemas predict more risky behaviors.

Conclusions

Designing prohealth policies requires further elaboration on the relation of psychosocial factors to preventive behaviors.

LEARNING OUTCOMES

  • Upon reading this article, the professionals designing health policies from the workplace to the global level are expected to more effectively integrate psychosocial factors in policy design with regard to any possible pandemics through interdisciplinary work

  • Upon reading this article, health care professionals are expected to develop more effective strategies targeting specific psychosocial profiles for increasing compliance with infection control measures in and outside the hospital during and after the COVID-19 pandemic.

Even during the first wave of the COVID-19 pandemic, health care workers were at high risk of infection. A meta-analysis covering a review of the data from China, United States, Germany, Netherlands, and Spain from February 2020 to June 2020 reported 51.7% of the health care workers to have tested positive.1 While some infections were related to their working environment in the hospital, some were related to their social lives and contacts with the household.2,3 It is reported that measures, such as using masks, social distance in social life, and appropriate masks use, glasses, gloves, and aprons in patient care are very effective in preventing the transmission of the disease.4,5 In addition, it is estimated that the prevention of severe infections and the prevention of deaths have been possible with the development and widespread use of vaccines.6 Increasing compliance with these measures quickly, both in the community and in hospitals, is of critical importance in the management of the pandemic.7

However, during the COVID-19 pandemic, several problems were reported in both protection measures and vaccination.8,9 Psychosocial factors are among the reported factors that affect health-related maladaptive behaviors.1015 Given that effectiveness of the transmitted messages might be enhanced by considering the psychological characteristics16 and the values one holds;17 persuasion capacity might be enhanced via tailor-made policies targeting different groups, which would be beneficial for public health in general and occupational health and safety in particular.

Psychosocial factors are reported to have notable links with adherence to preventive measures and with infections due to contagious diseases: Maladaptive personality structures including psychopathy,1820 narcissism,21 and borderline personality disorder22 predict higher risk behaviors for transmitting HIV. As for the normal range personality traits, mainly agreeableness23,24 and conscientiousness23 predict prohealth behaviors.

Previous studies find vaccination to be related to its perceived benefits and barriers25 and several psychosocial factors.2629 A positive association of provaccination with confidence in the vaccine,27,28 perceived risk, anticipated regret,26 altruistic concerns (protecting others),29 collective responsibility,28 likeliness to obtain pandemic-related information from traditional and authoritative sources16 is reported. A negative association of vaccination with age28; suspiciousness of vaccine's effectiveness, concern about safety,26 and complacency27,28 is reported. Vaccine hesitation is found to be higher also among those having at least one chronic disease.30

While compliance with the restrictions is found to vary by perceptions of the COVID-19 situation more than personality; a positive correlation with negativity and a negative correlation with mating (out of the situational eight); and a positive correlation with agreeableness (out of the Big Five) and a negative correlation with the Dark Triad, specifically with the Factor 1 psychopathy being related to shallow affect and lack of empathy rather than the Factor 2 psychopathy being related to impulsiveness and irresponsibility, with narcissistic rivalry rather than admiration, and with Machiavellianism are reported.31

Previous studies found perceptions of risk to be associated with attitudes toward COVID-19 prevention measures.3234 For age, contradictory results are reported. Although on the one hand older age is found to result in a higher perception of severity, trust in the authorities,35 and compliance to COVID-19 preventive measures36; it is also reported that protective behaviors decline with older age, and, that perceived risk is lower among the older aged compared with the middle-aged. Perceived risk and protective behaviors are lower among men than women.14

COVID-19 prevention intentions/behaviors increase with moral concerns (fairness vice, purity vice, authority virtue), collectivism, anger, disgust,10 optimism, anxiety, and fear of death; and decrease with social isolation,14 individualism, happiness,10 risk aversion, self-efficacy,32,37 altruistic concerns (concern for others),32 Dark Triad traits,12 and specifically antisocial traits (especially relatively low empathy, high callousness, deceitfulness, risk-taking).11

More precisely, previous studies found that social distancing is positively related to female sex and anxiety27 and negatively related to antisociality.13 Mask use increases with collectivism (as against individualism)38 and decreases with the dislike of forced mask-wear (psychological reactance), and the belief in the ineffectiveness of the masks.15 A network analysis reports the negative attitudes toward masks, vaccination, social distancing, political conservatism and the belief in the exaggeration of the COVID-19 threat to have connections with each other.15 Supporting the prescribed behaviors, such as handwashing and distancing, is positively related to trust in governments and trust in science, and is negatively related to trust in citizens39 and conspiratorial beliefs.40 Adherence to quarantine is associated with knowledge, perceived risk, perceived benefits, and financial concerns, among others.24 Compliance with protective measures varies by occupation. Compared with non–health care professionals, health care professionals have higher knowledge and higher compliance concerning hygiene and social distancing.41

Given the results of previous studies, for hospital staff, we investigate the relation of basic human values, personality, and sociodemographic variables (age, sex, education, occupation) to COVID-19 contraction, vaccination, and preventive health behavior in and outside work. A positive association of the self-transcendence (universalism, benevolence) and conservation (security, conformity, tradition) dimensions of the basic human values, and a negative association of the self-enhancement (power, achievement, partially hedonism) and openness to change (self-direction, stimulation partially hedonism) dimensions of the basic human values with the preventive health behavior are expected. Also, we expect preventive health behaviors to be positively predicted by agreeableness and conscientiousness; and negatively predicted by emotional stability, extraversion, the Dark Triad (narcissism, Machiavellianism, and psychopathy), and early maladaptive schemas. We expect power, stimulation, conscientiousness, and agreeableness to mediate the relation of maladaptive personality structures and schemas with preventive behaviors. We also expect basic human values to mediate the relation of personality with COVID-19 preventive behaviors. Ethical approval for this study was obtained from the Clinical Research Ethical Committee of Yildirim Beyazit University Yenimahalle Research and Training Hospital (Decision number and date: E-2021-45; 14 July 2021).

METHODS

Participants

The questionnaire form was administered in a training and research hospital that accepted COVID-19 patients since March 2020. For the purpose of ensuring anonymity, questionnaire forms were distributed and received in closed envelops through hospital units in August to October 2021. Name and other information, which might reveal the respondent's identity, were not asked. All respondents were clearly informed of the purpose of the study and were asked whether they consent or not at the beginning of the questionnaire form. After excluding those who did not give their consent and those who marked the form either inconsistently or systematically (for example marking “strongly agree” for all responses) 294 respondents (nmale = 65; nfemale = 220; nmisingvaluesforsex = 9) were included in the analysis. 5.4% are physician (n = 16); 37.4% are nurse (n = 110); 14.3% are other health workers (n = 42); 31.3% are nonhealth workers (n = 92); and 11.6% did not specify their occupation (n = 34).

Measures

Sociodemographic Indicators

Data for age (n = 31 for 18–24; n = 66 for 25–34; n = 117 for 35-44; n = 73 for 45–54; n = 6 for 5 5–64; n = 0 for 65–75 and above 75) and education (n = 79 for high school and below; n = 46 for associate degree; n = 133 for undergraduate degree; n = 34 for graduate degree) is collected on an ordinal scale, and is recoded into an interval scale (min = 1, max = 5 for age; min = 1 max = 4 for education). Data for occupation is collected in eight categories (n = 16 for physician; n = 110 for nurse; n = 11 for health officer; n = 20 for health technician; n = 31 for cleaning staff; n = 14 for official; n = 29 for IT officer; n = 52 for other to be specified). After adding those who did not specify their occupation to missing values, of 260 of those who specified their occupation, 64.6% are recoded as health worker (n = 168), 35.4% are recoded as non–health worker (n = 92) to be used in statistical analyses.

Behaviors on the Mask–Hygiene–Distance

Self-reported preventive behaviors on the mask use, hygiene, physical/social distance are measured by 16 individual items on a 5-point scale (1, never; 5, always). Most are positively worded items (for example, “I wash my hands before I eat”) while there are also certain negatively worded items (for example, “At my workplace, there are times when I take off my mask with my colleagues, even if there is not a distance of at least a meter between us”). Supplemental Digital Content (SDC) provides a list of all items (Supplemental Table S1, http://links.lww.com/JOM/B217).

Big Five Personality Questionnaire

We use the Turkish version of the 50-item Big Five Personality Questionnaire42 adapted from Goldberg's markers.43,44 Extraversion, agreeableness, conscientiousness, emotional stability, and intellect/imagination are measured on a 5-point scale (α = 0.769).

Young Schema Questionnaire Short Form 3

We use the Turkish version of the 90-item Young Schema Questionnaire Short Form 3 developed by Young and his colleagues.45 It covers 18 Early Maladaptive Schemas: emotional deprivation; abandonment, mistrust/abuse, social isolation, defectiveness/shame, failure, dependence/incompetence, vulnerability to harm and illness, enmeshment, subjugation, self-sacrifice, emotional inhibition, unrelenting standards, entitlement, insufficient self-control/self-discipline, approval-seeking/recognition-seeking, negativity/pessimism, and punitiveness. Each schema is measured by five items on a 6-point scale (α = 0.964).

Schwartz's Basic Human Values Scale

The 21-item Schwartz's Basic Human Values Scale measures 10 basic human values (benevolence, universalism, self-direction, stimulation, hedonism, achievement, power, security, conformity, and tradition) on a 6-point scale (α = 0.856). Its Turkish version is taken from the European Social Survey.46 Higher scores refer to a stronger adherence to the relevant value due to reverse coding, while centered scores are used in a consistent manner with Schwartz.47

Short Dark Triad

The Short Dark Triad (α = 0.813), developed by Jones and Paulhus,48 measures narcissism (mainly with reference to grandiosity, entitlement, and exhibitionism), Machiavellianism (mainly with reference to cynicism, strategic calculation, and manipulativeness) and psychopathy (mainly with reference to antisocial behavior, erratic lifestyle, and callous affect) on a five-point scale by nine items for each. We use its Turkish version.49

Statistical Analysis

Statistical analyses except for mediation are made with SPSS (IBM SPSS Statistics23). Mediation analyses (Delta method standard errors, bias-corrected percentile bootstrap confidence intervals) are made with JASP 0.16.2. After evaluating descriptive statistics, zero-order correlations are done as the grounds for further analyses. For the purpose of exploring the relation of psychosocial indicators with having COVID-19 infection (yes-no) and having COVID-19 vaccine (yes-no), a series of binary logistic regressions are performed. Independent-samples t-test is administered for examining whether socialization patterns and preventive behavior vary by sex and occupation. Standardized coefficients are reported for single linear regression analyses. Based on their results, a series of single mediation analyses are made. Based on their results, analyses for multiple mediators are performed. In the Bootstrap analyses through 1000 replications for testing the mediation effects, unstandardized estimates are used.

RESULTS

After excluding the missing values, the valid percent of those who reported that they have at least one chronic disease is 22.7% (n = 65; nfemale = 54; nage45&above = 27; nhighschoold&below = 17; nhealthworker = 36), those who reported that they had previously contracted COVID-19 disease is 38.5% (n = 110; nfemale = 81; nage45&above = 23; nhighschoold&below = 32; nhealthworker = 69), those who reported that they didn't have a vaccination for COVID-19 disease is 8.4% (n = 24; nfemale = 17; nage45&above = 1; nhighschoold&below = 5; nhealthworker = 14). Among those who got COVID-19 disease, 9.1% (n = 10) were not vaccinated, while 43.2% (n = 38; nfemale = 30; nage45&above = 12; nhighschoold&below = 10; nhealthworker = 22) stated that they got it from the patient or the patient's relatives; 12.5% (n = 11; nfemale = 6; nage45&above = 3; nhighschoold&below = 7; nhealthworker = 3) stated that they got it from colleagues at work; 13.6% (n = 12; nfemale = 12; nage45&above = 1; nhighschoold&below = 6; nhealthworker = 8) stated that they got it from the household. The remaining ones either stated other sources for COVID-19 infection or stated that they do not know the source.

The odds of being infected by COVID-19 increases by 1.543 (B = 0.434, S.E. = 0.191, P = 0.023, odds ratio = 1.543), for a unit increase in the self-direction score. The odds of being vaccinated increases by age and conformity, and decreases by emotional stability. For a unit increase in the age, conformity, and emotional stability scores, the odds of being vaccinated is respectively 2.083 times (B = 0.734, S.E. = 0.227, P = 0.001, odds ratio = 2.083), 1.778 times (B = 0.575, S.E. = 0.274, P = 0.036, odds ratio = 1.778), and 0.935 times (B = −0.067, S.E. = 0.033, P = 0.039, odds ratio = 0.935) the odds of not being vaccinated.

Age is positively associated with having a chronic disease (r = 0.239, n = 285, P = 0.000) and vaccine doses (r = 0.380, n = 285, P = 0.000). As age increases, a person more frequently resorts to several preventive measures and acts less risky (Supplemental Table S2, SDC, http://links.lww.com/JOM/B217): one more frequently eats alone and wears proper masks during contact with patients at the workplace; wears masks and keeps at least a meter distance when someone visits home; and one less frequently socialize indoors with friends and relatives; go to shopping malls, cafes, and restaurants.

The socialization patterns and keeping track of preventive measures vary also by sex, increasing the risk of contagion for male hospital workers: During the pandemic, men (M = 3.05, SD = 1.227) saw their relatives and friends at home more frequently than the women (M = 2.66, SD = 1.043); (t(281) = −2.492, P = 0.013). At home, men (M = 3.33, SD = 1.369) kept at least a meter distance less frequently than the women (M = 3.70, SD = 1.248); (t(281) = 2.068, P = 0.040). At the hospital, men (M = 4.30, SD = 1.200) use protective equipment (other than masks) less frequently than the women (M = 4.57, SD = 0.872); (t(280) = 1.973, P = 0.049).

In addition, the socialization patterns and keeping track of preventive measures vary by occupation: As can be expected, health workers (M = 4.67, SD = 0.670) use the recommended type of mask during contact with the patient more frequently than the non-health workers (M = 4.41, SD = 1.059); (t(128.145) = −2.126, P = 0.035). Health workers (M = 4.68, SD = 0.612) also use other protective equipment as recommended during patient care more frequently than the non–health workers (M = 4.24, SD = 1.306); (t(108.928) = −3.026, P = 0.003). Still, non–health workers (M = 4.04, SD = 1.219) warn another without a mask to wear one more frequently than the health workers (M = 3.58, SD = 1.236); (t(257) = 2.914, P = 0.004).

Education is associated with the socialization patterns and preventive measures (Supplemental Table S2, SDC, http://links.lww.com/JOM/B217): The higher the education level is, the higher the frequency of keeping at least a meter distance when someone visits home; the more one does not stay with anyone without a mask (except for the household) indoors; yet, at work, the less frequently one uses hand sanitizer and the less frequently one warns another without a mask to wear one; and the less frequently one applies to the Personnel Health in case of a risky contact with a COVID-19 patient.

Those with chronic diseases are also slightly more watchful on certain issues. Those with at least one chronic disease (M = 3.27, SD = 1.324) more frequently wear masks when someone visits home than those without chronic diseases (M = 2.84, SD = 1.374); (t(283) = −2.191, P = 0.029). When someone visits home, those with chronic diseases (M = 4.06, SD = 1.176) also keep at least a meter distance more frequently than those without chronic diseases, (M = 3.52, SD = 1.260); (t(282) = −3.037, P = 0.003). Eating alone at work is more prevalent among those with chronic diseases (M = 2.94, SD = 1.180) compared with those without chronic diseases (M = 2.57, SD = 1.156); (t(283) = −2.201, P = 0.029). At work, those with chronic diseases (M = 4.13, SD = 1.047) also more frequently warn others without a mask to wear one than those without chronic diseases (M = 3.67, SD = 1.298); (t(124.535) = −2.866, P = 0.005).

Several human values and personality characteristics weakly or moderately, but consistently predict most of those behaviors concerning protection (Supplemental Tables S2 and S3, SDC, http://links.lww.com/JOM/B217). The general pattern indicates that self-transcendence and conservation dimensions of the basic human values—particularly universalism, benevolence, security, tradition, and conformity—and the agreeableness and conscientiousness dimensions of the Big Five predict more preventive and less risky behaviors. Self-enhancement and openness to change dimensions of the basic human values—particularly power, achievement, hedonism, self-direction, stimulation-, the Dark Triad—specifically narcissism, Machiavellianism and psychopathy-, and 16 of the 18 early maladaptive schemas—emotional deprivation, abandonment, mistrust/abuse, social isolation, defectiveness/shame, failure, dependence/incompetence, vulnerability to harm and illness, enmeshment, subjugation, self-sacrifice, emotional inhibition, entitlement, insufficient self-control/self-discipline, approval-seeking/recognition-seeking, negativity/pessimism- predict less preventive and more risky behaviors. Emotional stability negatively predicts warning others to wear a mask, while intellect/imagination positively predicts eating together with proper distance and using disinfectant for hands at work.

The most recurrent mediators are conscientiousness among the Big Five (Supplemental Table S4, SDC, http://links.lww.com/JOM/B217) and power among the basic human values (Supplemental Table S6, SDC, http://links.lww.com/JOM/B217). Also, among the Big Five agreeableness, emotional stability, intellect/imagination, and extraversion (Supplemental Table S5, SDC, http://links.lww.com/JOM/B217); among the basic human values achievement (Supplemental Table S6, SDC), stimulation, self-direction (Supplemental Table S7, SD, http://links.lww.com/JOM/B217C), universalism, benevolence (Supplemental Table S8, SDC, http://links.lww.com/JOM/B217), security, tradition, conformity (Supplemental Table S9, SDC, http://links.lww.com/JOM/B217); and among the maladaptive personality structures and schemas Machiavellianism, psychopathy, emotional deprivation, and self-sacrifice (Supplemental Table S10, SDC, http://links.lww.com/JOM/B217) mediate the relationship between the psychosocial factors and socialization patterns / preventive behaviors.

No mediators appeared for the outcomes item 6 (I do not stay indoors with anyone without a mask, except for the people I live with at home) and item 10 (At my workplace, I eat with others by keeping the appropriate distance). In univariate regression analyses (Supplemental Tables S2 and S3, SDC, http://links.lww.com/JOM/B217), item 6 is positively predicted by education, conscientiousness and being a woman, whereas item 10 is positively predicted by intellect/imagination and Machiavellianism.

Supplemental TABLE S11 (SDC, http://links.lww.com/JOM/B217) summarizes the analyses by multiple mediators and the remaining individual mediators. The general pattern is as such: As certain early maladaptive schemas become more dominant; one becomes less conscientious and aggregable, one values power and stimulation more, increasing the frequency of a variety of risky behaviors. As one has stronger Dark Triad traits; certain early maladaptive schemas become more dominant, conscientiousness and agreeableness decrease, one values power and stimulation more and security less, increasing the frequency of a variety of risky behaviors. Except for a few exceptions, the pattern is similar within and outside the hospital.

DISCUSSION

This study collected data from a hospital accepting COVID-19 patients, where not only the health care professionals but also other personnel received training on COVID-19 and preventive measures during the pandemic. Therefore, our sample composed of hospital staff differs from those groups without such training. Results have to be interpreted within that scope.

For the sample analyzed, a good many psychosocial factors are found to predict compliance to preventive behaviors and socialization patterns consistently, although with slight to moderate effect. While no statistically significant relations between the frequency of preventive behaviors and COVID-19 contraction appeared, which might be on account of those having the household and close ones as the source of infection, self-direction predicted COVID-19 contraction. Those who have higher self-direction scores are more likely to contract COVID-19 while they less frequently eat alone and wear masks at work. These findings are parallel to previous research indicating a negative relationship between psychological reactance and mask use.15 Therefore, considering the possibility of psychological reactance in the design of occupational prohealth training would increase the effectiveness of the transmitted messages.

While for our sample, the 55- to 64-year-old hospital workers were only six and those older than 65 years were absent, our finding that older age predicts vaccination and 7 of 16 protective/lower risk behaviors is compatible with various research,35,36 except for some.14,28 Inconsistency in a variety of studies might be on account of the under-represented age groups among other sampling-related factors. Single mediation analyses indicate that the direct effect of age remains, while there are partial mediations concerning two behaviors. As one grows older, one values tradition more and stimulation less and also becomes less Machiavellist, decreasing the frequency of going to such crowded places as cafes and restaurants. In addition, as one grows older, conformity increases, which in turn increases the frequency of eating alone at work. Given the results, making certain prohealth messages more appealing to specific age groups would support protective measures further.

Our finding that being a woman predicts less risky and more preventive behaviors for 4 of the 16 protective/lower risk behaviors is compatible with previous research.14,27 Mediation analyses indicated that since men are less agreeable, violation of the distance rule in the presence of guests at home is more. Men more frequently meet with friends or relatives indoors on account of lower conscientiousness and higher psychopathy. Men use other protective equipment during patient care at work less due to higher emotional deprivation and lower conscientiousness. Appealing messages for this profile would enhance prohealth behaviors.

Our finding that the more educated more frequently follow the distance rule at home was in the expected direction, indicating a need for higher comprehensibleness of the transmitted messages for those with lower education. However, the finding that the more educated less frequently use hand disinfectant and inform authorities after a risky contact with the patient requires future research for uncovering the underlying factors.

Our finding that the frequency of warning those without a mask decreases with higher education and being a health care professional, and increases with having a chronic disease might have relevance to the tendency to refrain from possible aggressive reactions unless it is worth it. Besides, those who report being more agreeable and conscientious, and attribute less value to power perform this behavior more frequently. Although higher emotional stability principally results in less frequently warning those without a mask, the mediation analysis indicates that, for some, as emotional stability increases, one values power less, resulting in warning others more. The finding that emotional stability decreases the odds of being vaccinated is also comparable to those studies reporting a negative relationship between vaccination and complacency.27,28

Our finding that complying with preventive measures and performing less risky behaviors increase by the self-transcendence and conservation values, agreeableness, and conscientiousness, and decrease by the self-enhancement and openness to change values, the Dark Triad traits, and early maladaptive schemas is in the expected direction, and is comparable to the previous studies.1823 The predominance of conscientiousness and power as the most recurrent mediators points to a need for designing policies that would improve conscientiousness, which is shown to be possible,50 and that would decrease the need for power, which might require long-term strategies including effective psychological and cultural interventions.

Given that previous research reports antisociality to be associated with leaving home more frequently and standing closer to others, health risks increase not only for the antisocial individuals but also for the community in the case of COVID-19.13 In support of the previous studies11,13,1820 we also found higher psychopathy to end in more risky behaviors (predicting 5 of 16 behaviors). Still, concerning keeping the proper distance when someone visits home, while the direct effect of psychopathy appeared to strongly decrease the frequency of this behavior, the indirect effect through the self-sacrifice schema slightly increase compliance to the distance rule, reminding one of the successful psychopathy.51 Still, given that psychopathy positively correlates with all earlier maladaptive schemas in our sample, it would be beneficial to support lifelong sociopsychological interventions for healing dysfunctional schemas in a way to replace maladaptive coping styles (surrender, avoidance, overcompensation) with more adaptive responses.52

Alternatives that appear to be a compromise between the pre-pandemic socialization patterns and post-pandemic protective measures can be encouraged especially for the ones with maladaptive psychological orientations. Since we found that eating with others by keeping the appropriate distance is positively predicted by not only normal range personality traits, but also approval-seeking/recognition-seeking schema and Machiavellianism, and also that socialization outdoors included narcissism as a predictor, being fully mediated by extraversion; it would be functional to encourage novel socialization patterns that would serve as a compromise. Effective instruments that make such patterns appealing for those with higher maladaptive psychological orientations might be adapted through interdisciplinary teamwork, with the acknowledgment that high-risk behaviors might themselves become stimulating for some, the psychopaths in the first place.53

Future studies might explore effective instruments to increase compliance with the preventive measures targeting specific groups of individuals with varying profiles. This requires interdisciplinary work benefiting from neuroscience, psychology, communication sciences, sociology, arts, architecture, engineering, and several branches of medicine among others. Re-designing the workplaces, socialization spaces and patterns in a way to minimize the risk of infection would prove to be functional during any possible pandemic. Exploring efficient ways to increase the prohealth behaviors of those individuals with different values, personality orientations, emotional states, and sources of motivation (eg, psychopaths predominantly being motivated by rewards) requires interdisciplinary short-term and long-term planning from the workplaces to the international organizations.

CONCLUSION

All in all, improving occupational health requires an integrative approach with tailor-made measures targeting specific profiles in and outside work during any possible pandemic. Exploration of psychosocial factors helps to design tailor-made policies targeting groups of individuals with varying characteristics. A multidimensional design of such short-term and long-term measures would prove to be beneficial not only at the workplace but also at the global level, given the contagiousness of infectious agents.

Footnotes

Fatma Ülkü Selçuk ORCID NO: 0000-0003-2523-9387

Semiha Solak Grassie ORCID NO: 0000-0002-1123-3454

Conflicts of interest: None declared.

Funding sources: None to disclose.

Ethical Approval: Ethical approval for this study was obtained from the Clinical Research Ethical Committee of Yildirim Beyazit University Yenimahalle Research and Training Hospital (Decision number and date: E-2021-45; 14 July 2021).

Supplemental digital contents are available for this article. Direct URL citation appears in the printed text and is provided in the HTML and PDF versions of this article on the journal’s Web site (www.joem.org).

REFERENCES

  • 1.Gholami M Fawad I Shadan S, et al. COVID-19 and healthcare workers: a systematic review and meta-analysis. Int J Infect Dis. 2021;104:335–346. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2.Lai X Wang M Qin C, et al. Coronavirus disease 2019 (COVID-19) infection among health care workers and implications for prevention measures in a tertiary hospital in Wuhan, China. JAMA Netw Open. 2020;3:e209666. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3.Gómez-Ochoa SA Franco OH Rojas LZ, et al. COVID-19 in health-care workers: a living systematic review and meta-analysis of prevalence, risk factors, clinical characteristics, and outcomes. Am J Epidemiol. 2021;190:161–175. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4.Chung-Cheng VC, Wong SC, Yuen KY. Estimating coronavirus disease 2019 infection risk in health care workers. JAMA Netw Open. 2020;3:e209697. [DOI] [PubMed] [Google Scholar]
  • 5.Wang DD O’Neil WW Zervos MJ, et al. Association between implementation of a universal face mask policy for healthcare workers in a health care system and SARS-CoV-2 positivity testing rate in healthcare workers. J Occup Environ Med. 2021;63:476–481. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.Tan ST Park JH Rodríguez-Barraquer I, et al. COVID-19 vaccination and estimated public health impact in California. JAMA Netw Open. 2022;5:e228526. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.Rajan S McKee M Hernandez Quevedo C, et al. What have European countries done to prevent the spread of COVID-19? Lessons from the COVID-19 health system response monitor. Health Policy. 2022;126:355–361. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8.Khubchandani J, Sharma S, Price JH, Wiblishauser MJ, Sharma M, Webb FJ. COVID-19 vaccination hesitancy in the United States: a rapid national assessment. J Community Health. 2021;46:270–277. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.Frank C, Dorrough AR, Schneider IK. Ambivalence and adherence to preventive measures During the COVID-19 pandemic: data From the U.S. And Germany. Data Brief. 2022;42:108124. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10.Liu Z, Geng H, Chen H, Zhu M, Zhu T. Exploring the mechanisms of influence on COVID-19 preventive behaviors in China’s social media users. Int J Environ Res Public Health. 2020;17:8766. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.Miguel KF, Machadob GM, Pianowskib G, Carvalhob LF. Compliance With containment measures to the COVID-19 pandemic over time: do antisocial traits matter? Personal Individ Differ. 2021;168:110346. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.Nowak B, Brzóska P, Piotrowski J, Sedikides C, Żemojtel-Piotrowska M, Jonason PK. Adaptive and maladaptive behavior during the COVID-19 pandemic: the roles of dark triad traits, collective narcissism, and health beliefs. Personal Individ Differ. 2020;167:110232. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.O'Connell K, Berluti K, Rhoads SA, Marsh AA. Reduced social distancing early in the COVID-19 pandemic is associated with antisocial behaviors in an online United States sample. PLoS One. 2021;16:e0244974. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.Pasion R, Paiva TO, Fernandes C, Barbosa F. The age effect on protective behaviors During the COVID-19 outbreak: sociodemographic, perceptions and psychological accounts. Front Psychol. 2021;11:561785. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Taylor S, Asmundson GJG. Negative attitudes about facemasks during the COVID-19 pandemic: the dual importance of perceived ineffectiveness and psychological reactance. PLoS One. 2021;16:e0246317. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16.Murphy J Vallières F Bentall RP, et al. Psychological characteristics associated With COVID-19 vaccine hesitancy and resistance in Ireland and the United Kingdom. Nat Commun. 2021;12:29. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.Albarracin D, Jung H. A research agenda for the post-COVID-19 world: theory and research in social psychology. Asian J Soc Psychol. 2021;24:10–17. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18.Benotsch EG Rodríguez VM Hood K, et al. Misleading sexual partners about HIV status among persons living with HIV/AIDS. J Community Health. 2012;37:1049–1057. [DOI] [PubMed] [Google Scholar]
  • 19.Kelley JL, Petry NM. HIV risk behaviors in male substance abusers with and without antisocial personality disorder. J Subst Abus Treat. 2000;19:59–66. [DOI] [PubMed] [Google Scholar]
  • 20.Ladd GT, Petry NM. Antisocial personality in treatment-seeking cocaine abusers: psychosocial functioning and HIV risk. J Subst Abus Treat. 2003;24:323–330. [DOI] [PubMed] [Google Scholar]
  • 21.Martin AM, Benotsch EG, Lance SP, Green M. Transmission risk behaviors in a subset of HIV-positive individuals: the role of narcissistic personality features. Personal Individ Differ. 2013;54:256–260. [Google Scholar]
  • 22.Adams LM, Stuewig JB, Tangney JP. Relation of borderline personality features to preincarceration HIV risk behaviors of jail inmates: evidence for gender differences? Personal Disord. 2016;7:40–49. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Blagov PS. Adaptive and dark personality in the COVID-19 pandemic: predicting health-behavior endorsement and the appeal of public-health messages. Soc Psychol Personal Sci. 2021;12:697–707. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.Webster RK, Brooks SK, Smith LE, Woodland L, Wessely S, Rubin GJ. How to improve adherence with quarantine: rapid review of the evidence. Public Health. 2020;182:163–169. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25.Walker NA, Zhang T, Peng X, Ge J, Gu H, You H. Vaccine acceptance and its influencing factors: an online cross-sectional study among international college students studying in China. Vaccines (Basel). 2021;9:585. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26.Brewer NT, Chapman BG, Rothman AJ, Leask J, Kempe A. Increasing vaccination: putting psychological science into action. Psychol Sci Public Interest. 2018;18:149–207. [DOI] [PubMed] [Google Scholar]
  • 27.Kwok KO Li KK Tang A, et al. Psychobehavioral responses and likelihood of receiving COVID-19 vaccines during the pandemic. Emerg Infect Dis. 2021;27:1802–1810. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28.Kwok KO, Li KK, Wei WI, Tang A, Wong S, Lee SS. Influenza vaccine uptake, COVID-19 vaccination intention and vaccine hesitancy among nurses: a survey. Int J Nurs Stud. 2021;114:103854. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29.Tavolacci MP, Dechelotte P, Ladner J. COVID-19 vaccine acceptance, hesitancy, and resistancy among university students in France. Vaccines (Basel). 2021;9:654. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30.Ghazy RM ElHafeezS A Shaaban R, et al. Determining the cutoff points of the 5c scale for assessment of COVID-19 vaccines psychological antecedents among the Arab population: a multinational study. J Prim Care Community Health. 2021;12:21501327211018568. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 31.Zajenkowski M, Jonason PK, Leniarska M, Kozakiewicz Z. Who complies With the restrictions to reduce the spread of COVID-19?: personality and perceptions of the COVID-19 situation. Personal Individ Differ. 2020;166:110199. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 32.Ayre J Cvejic E McCaffery K, et al. Contextualising COVID-19 prevention behaviour over time in Australia: Patterns and long-term predictors from April to July 2020 in an online social media sample. PLoS One. 2021;16:e0253930. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33.Bruin BW, Bennett D. Relationships between initial COVID-19 risk perceptions and protective health behaviors: a national survey. Am J Prev Med. 2020;59:157–167. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 34.Eichenberg C, Grossfurthner M, Andrich J, Hübner L, Kietaibl S, Holocher-Benetka S. The relationship between the implementation of statutory preventative measures, perceived susceptibility of COVID-19, and personality traits in the initial stage of corona-related lockdown: a German and Austrian population online survey. Front Psychol. 2021;12:596281. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 35.Moussaoui LS, Ofosu ND, Desrichard O. Social psychological correlates of protective behaviours in the COVID-19 outbreak: evidence and recommendations From a nationally representative sample. Appl Psychol Health Well Being. 2020;12:1183–1204. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 36.Cerami C Galandra C Santi GC, et al. Risk-aversion for negative health outcomes may promote individual compliance to containment measures in Covid-19 pandemic. Front Psychol. 2021;12:666454. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 37.Scholz U, Freund AM. Determinants of protective behaviours during a nationwide lockdown in the wake of the COVID-19 pandemic. Br J Health Psychol. 2021;26:935–957. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 38.Lu JG, Jin P, English AS. Collectivism predicts mask use during COVID-19. Proc Natl Acad Sci. 2021;118:e2021793118. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 39.Pagliaro S Sacchi S Pacilli MG, et al. Trust predicts COVID-19 prescribed and discretionary behavioral intentions in 23 countries. PLoS One. 2021;16:e0248334. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 40.Teovanović P, Lukić P, Zupan Z, Lazić A, Ninković M, Žeželj I. Irrational beliefs differentially predict adherence to guidelines and pseudoscientific practices during the COVID-19 pandemic. Appl Cogn Psychol. 2021;35:486–496. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 41.Shah SU Xiu Ling Loo E En Chua C, et al. Association between well-being and compliance with COVID-19 preventive measures by healthcare professionals: a cross-sectional study. PLoS One. 2021;16:e0252835. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 42.Tatar A. Büyük Beş-50 Kişilik Testinin Türkçeye çevirisi ve Beş Faktör Kişilik Envanteri Kisa Formu ile karşilaştirilmasi. Anadolu Psikiyatri Dergisi. 2017;18:51–61. [Google Scholar]
  • 43.Goldberg LR. The development of markers for the big-five factor structure. Psychol Assess. 1992;4:26–42. [Google Scholar]
  • 44.International Personality Item Pool . Administering IPIP Measures, with a 50-item Sample Questionnaire (no date). Available at: https://ipip.ori.org/New_IPIP-50-item-scale.htm. Accessed May 30, 2021.
  • 45.Soygüt G, Karaosmanoğlu A, Çakir Z. Erken Dönem Uyumsuz Şemalarin Değerlendirilmesi: Young Şema Ölçeği Kisa Form-3'ün psikometrik özelliklerine ilişkin bir inceleme. Turk Psikiyatri Derg. 2009;20:75–84. [PubMed] [Google Scholar]
  • 46.European Social Survey . The European Social Survey supplementary questionnaire F-2-F A (Round 2 2004). Available at: https://www.europeansocialsurvey.org/docs/round2/fieldwork/turkey/ESS2_supplementary_questionnaire_a_TR.pdf. Accessed May 30, 2021.
  • 47.Schwartz SH. Computing scores for the 10 human values (no date). Available at: https://www.europeansocialsurvey.org/docs/methodology/ESS_computing_human_values_scale.pdf. Accessed May 30, 2021.
  • 48.Jones DN, Paulhus DL. Introducing the short dark triad (SD3): a brief measure of dark personality traits. Assessment. 2014;21:28–41. [DOI] [PubMed] [Google Scholar]
  • 49.Özsoy E, Rauthmann JF, Jonason PK, Ardiç K. Reliability and validity of the Turkish versions of dark triad dirty dozen (DTDD-T), short dark triad (SD3-T), and single item narcissism scale (SINS-T). Personal Individ Differ. 2017;117:11–14. [Google Scholar]
  • 50.Hudson NW. Does successfully changing personality traits via intervention require that participants be autonomously motivated to change? J Res Pers. 2021;95:104160. [Google Scholar]
  • 51.Benning SD, Venables NC, Hall JR. Successful psychopathy. In: Patrick CJ, ed. Handbook of Psychopathy.  : The Guilford Press; 2018:585–608. [Google Scholar]
  • 52.Young JE, Klosko JS, Weishaar ME. Schema Therapy: A Practitioner's Guide. Guilford Press; 2003. [Google Scholar]
  • 53.Hare RD. Without Conscience: The Disturbing World of the Psychopaths Among Us. New York: Pocket Books; 1993. [Google Scholar]

Articles from Journal of Occupational and Environmental Medicine are provided here courtesy of Wolters Kluwer Health

RESOURCES